volume 3 article: mc03-0033-2003 edited by mary kalantzis...

The International Journal of Knowledge, Culture and Change Management

Volume 3

Article: MC03-0033-2003

Edited by Mary Kalantzis and Bill Cope

Proceedings of the Management Conference 2003

Internal Group Dynamics, Team Characteristics,and Team Effectiveness

A Preliminary Study Of Virtual Teams

T. Ramayah, Prof. Muhamad Jantan, Dr. Aizzat Mohd. Nasurdin, and Koay Hooi Ling

International Journal of Knowledge, Culture andChange Management,

Volume 3

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This journal and individual papers published at http://ManagementConference.Publisher-Site.com/a series imprint of theUniversityPress.com

First published in Australia in 2003/2004 by Common Ground Publishing Pty Ltd athttp://ManagementConference.Publisher-Site.com/

Selection and editorial matter copyright © Mary Kalantzis and Bill Cope 2003Individual chapters copyright © individual contributors 2003

All rights reserved. Apart from fair dealing for the purposes of study, research, criticism or review as permittedunder the Copyright Act, no part of this book may be reproduced by any process without written permission fromthe publisher.

ISSN: 1447-9524 (Print)ISSN: 1447-9575 (Online)

Cover design by Common Ground

Papers presented at the Third International Conference on Knowledge, Culture and Change in Organisations,Bayview Beach Resort, Penang, Malaysia, 11-14 August 2003.

EditorsMary Kalantzis, Faculty of Education, Language and Community Services,

RMIT University, Melbourne, Australia.Bill Cope, Centre for Workplace Communication and Culture, Australia.

Editorial Advisory BoardZainal Ariffin, Deputy Dean, Research and Graduate Studies, School of Management,

Universiti Sains Malaysia, Penang, Malaysia.Rob Brooks, Faculty of Business, RMIT University, Melbourne, Australia.Rod Dilnutt, William Bethwey and Associates, Melbourne, Australia.Judith Ellis, Enterprise Knowledge, Melbourne, Australia.David Hakken, Department of Social Science and Humanities, State University of New York

Institute of Technology, Utica, NY, USA.Margaret Jackson, Faculty of Business, RMIT University, Melbourne, Australia.Paul James, The Globalism Institute, RMIT University, Melbourne, Australia.Leslie Johnson, School of Business, University of Greenwich, UK.Krishan Kumar, Department of Sociology, University of Virginia, USA.Martyn Laycock, University of Greenwich and managingtransitions.net, UK.David Lyon, Queens University, Ontario, Canada.Bill Martin, Faculty of Business, RMIT University, Melbourne, Australia.Kirpal Singh, Creative Thinking Program, Singapore Management University, Singapore.Dave Snowdon, Cynefin Centre for Organisational Complexity, IBM Global Services, UK.

International Journal of Knowledge, Culture and Change Management, Volume 3 l www.ManagementJournal.Publisher-Site.comCopyright © Common Ground ISSN l 1447-9524 (Print) ISSN 1447-9575 (Online)Paper presented at the Third International Conference on Knowledge, Culture and Change in Organisations, Bayview Beach Resort, Penang, Malaysia,11-14 August 2003 l www. ManagementConference.com

Internal Group Dynamics, Team Characteristics,and Team Effectiveness

A Preliminary Study Of Virtual Teams

T. Ramayah, Prof. Muhamad Jantan, Dr. Aizzat Mohd. Nasurdin,and Koay Hooi Ling

Abstract

The advances in ICT and also the advent of the Internet have changed the way wework in the new millenium. Virtual teamworking has already been practisedextensively in the West but in the case of Malaysia, a developing country is stillstruggling to get a strong foothold. In lieu of the above this study looks at the impactof internal group dynamics, team characteristics on the effectiveness of a virtual teamamong manufacturing companies in the northern region of Malaysia. A questionnairesurvey was used to collect data from 152 virtual teams from the multinational firmsoperating in Penang. The findings showed that team characteristics do not impactinternal group dynamics or team effectiveness; while internal group dynamicscorrelates positively with virtual team effectiveness. Among the dimensions, it wasfound that team member relations correlates positively with both team performanceand team member satisfaction, while team leadership was found to correlatespositively with team member satisfaction. Thus it can be concluded that it is importantfor managers to maintain proper composition and characteristics of the virtual team,while concentrate more effort on the team member relations and team leadership topromote better team dynamics, Communications among team members need to behandled with care. Exessive communication using the wrong means, such aselectronic communications, may have negative effects and causes dissatisfactionamong team members. At the same time, increasingly, the conventional co-located(face-to-face) teams will endeavor to improve its performance and effectiveness byimitating some of the technologies and the characteristics of virtual team.

Introduction

Today, global virtual teams are playing an increasingly important role in internationalbusiness by offering organizations the opportunity for reaching beyond traditionalboundaries (Pauleen & Yoong, 2001). However, global, multicultural, inter-organizational, virtual teams and the effective use of information and communicationtechnologies (ICTs) present real and compelling challenges to its facilitators, as wellas presenting to the teams unparalleled opportunities for expanding on perspective,approaches, and ideas. While research shows that the development of personalrelationships between virtual team members is an important factor in effectiveworking relationships, little research has been conducted on the effects of crossingorganizational, cultural, time and distance boundaries on relationship building invirtual teams (Pauleen & Yoong, 2001). The use of virtual team has outpaced ourunderstanding of their dynamics and unique characteristics.

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Due to the rapid growth of virtual teams in many global organizations, especiallyto take advantage of the time zone differences by having product development teamacross all sites to work for 24 hours round the clock rather than the normal single site8 hours per day, the urge to understand more on virtual team effectiveness and itsinternal group dynamics has been significant. As such, this research attempts tounderstand more on the virtual team effectiveness, team dynamics as well as theinfluence from team characteristics such as team size and functional diversity on teamdynamics and team effectiveness. This research has been designed to test a generalhypothesis that virtual team effectiveness is influenced by internal group dynamicsand team characteristics. Although there have been some studies done in Westerncountries on related areas in different contexts and settings, most of these are inexperimental settings or in a more general perspective. This study attempts toconcentrate on the internal group dynamics based on the responses from virtual teammembers that are working in multi-national organizations in the northern region ofMalaysia.

Although there are various definitions of virtual teams, Lurey and Raisinghani(2001), Potter, Balthazard and Cooke(2000), and Andres (2002) have defined virtualteam as people who share a common purpose or goal or are given a specific task, andinteract interdependently (Lurey & Raisinghani, 2001) and collaboratively(Andres,2002; Potter et al, 2000) within a larger organizational setting, with membersdispersed across multiple sites(Andres, 2002), organizational, space, and/or timeboundaries (Lurey & Raisinghani, 2001), geographically distributed (Potter et al.,2000) and are often cross-functional in nature, from a variety of organizationaldepartments or business units. These teams have a low frequency of face-to-facecontact, and are able to collaborate through the use of emerging computer andcommunication technologies to enable the organizations to get projects done asquickly as possible while utilizing the skills of project team members that are fromdifferent areas of expertise and geographically dispersed (Lurey & Raisinghani, 2001;Potter et al, 2000).

This study is important in understanding the factors that contribute to the successof a virtual team. As the virtual team could possibly consist of individuals fromdifferent backgrounds, geographical locations and time zones, thus by nature thiscould enhance innovativeness of the team when well managed. In addition, theforming of virtual teams enables concurrent engineering for research and developmentteams (Bal & Teo, 2000), hence, reduces development time, ensuring time-to-marketfor new products and services. The significance of concurrent engineering has beenclearly proven as companies have switched from asking questions like “Whyconcurrent engineer?” to “How concurrent engineering?” in the ManagementRoundtable’s Seventh International Conference on Design for Manufacturability, heldin Orlando, Florida, USA (Tong & Fitzgerald, 1994).

Conceptual Foundation

The theoretical framework for this study (Figure 1) is adapted from the findings onliterature reviews done, especially as a subset of Lurey and Raisinghani’s empiricalstudy (2001) on best practices in virtual teams. Lurey and Raisinghani (2001) studiedall factors that contribute to or inhibit the success of a virtual team, including internalgroup dynamics, design process, and external support mechanisms. However, in this

Internal Group Dynamics, Team Characteristics, and Team EffectivenessT. Ramayah, Prof. Muhamad Jantan, Dr. Aizzat Mohd. Nasurdin, and Koay Hooi Ling

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study, only a few important dimensions of internal group dynamics’ impact on teameffectiveness have been considered.

In addition, according to Duarte and Snyder (2001), team characteristics have itsrole in determining the internal group dynamics. Thus, this research has added thiscomponent so as to understand further on how team size and the team’s functionaldiversity impact the internal group dynamics. At the same time, Pagell and LePine(2002) and a few other studies found that team characteristics actually influence teameffectiveness, thus the relationship of team characteristics, internal group dynamicsand team effectiveness has been modified to reflect this relationship, as depicted inFigure 1. This framework is based on the findings from the literature reviewed thatfollows:

Figure 1Theoretical frameworks for virtual team effectiveness and related variables.

Team Characteristics and Internal Group Dynamics

Duarte and Snyder (2001) stated that team dynamics are determined by complicatedvariables that relate to three factors: time, team environment, and team composition.Stoel (2002) in his study commented that group research generally showed that largeteam size has a negative impact on group dynamics. As cited in Stoel’s study, Shaw(1976), in an extensive review of group literature, noted that group size directlyinfluences group characteristics. In addition, he noted that group size directlyinfluence member behaviors in an inverse relationship; the larger the group, the lessfrequent the communication behavior of the group members. Mullen (1987, as citedby Stoel, 2002) reported results of two meta-analyses examining the relationshipbetween group size and group participation behaviors. The analyses showed thatparticipation in classroom and in religious groups declined as group size increased.

Virtual Team Effectiveness• Team Performance• Team Member Satisfaction

Internal Group Dynamics• Team Member Relations• Team Leadership• Face-to-face Communication• Social Communication• Electronic Communication

Team Characteristics• Team Size• Functional Diversity


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Similarly, Wagner (1987), as cited in Stoel’s study, in a study of participatorybehaviors in an assigned group project for a class showed that the smaller the group,the more members participated in project preparation behaviors.

As cited by Keller (2001), the use of cross-functional groups can result in negativeoutcomes such as increased costs (AitSahlia, Johnson & Will, 1995), felt stress, andlower group cohesiveness (Donnellon, 1996; Jehn, 1997; Swamidass & Aldridge,1996). Duarte and Snyder (2001) stressed that a person’s functional background cangreatly affect his or her behavior. Thus, a functionally diversified team with membersfrom various departments may potentially promote misunderstanding, and cause theteam to have task and social dynamics that keep it in the stages of problem solvingand conflict resolution. Church (1995), on his case study on diversity in workgroupsettings, shared similar opinion and stressed that this differences often create conflict,and when handled inappropriately, can result in poor performance. The discussionabove leads us to the first hypothesis and subhypotheses:

H1: Team characteristics correlates negatively with internal group dynamics.H1a: Team size correlates negatively with extent of team member relation.H1b: Team functional diversity correlates negatively with extent of team

member relation.H1c: Team size correlates negatively with quality of team leadership.H1d: Team functional diversity correlates negatively with extent of team

leadership.H1e: Team size correlates negatively with extent of face-to-face

communication.H1f: Team functional diversity correlates negatively with extent of face-to-face

communication.H1g: Team size correlates negatively with social communication.H1h: Team functional diversity correlates negatively with social

communication.H1i: Team size correlates negatively with electronic communication.H1j: Team functional diversity correlates negatively with electronic

ommunication.

Team Characteristics and Team Effectiveness

Past researches found that the lack of training or the wrong team composition willproduce critical skill gaps that will inevitably lead to a decrease in overall teamperformance (Castka, Bamber, Sharp & Belohoubek, 2001; Church, 1998). Stoel(2002) has shown that team size influences group outcomes. As cited by Stoel, inMullen (1987), a meta-analysis of classroom studies showed that as school class sizeincreased, student achievement decreased. Another study (Green et. al, 1996, as citedby Stoel, 2002) examining the relationship between group size and group outcome inthe workplace found a negative relationship between quality of the relationshipamong team members and both work group size and organization size. An empiricalstudy of rural hospital consortia done by Chan et al. (1999, as cited by Stoel, 2002)found a curvilinear relationship between group size and outcome measures. As groupsize increased, operating profit and revenue per admission increased until an optimumgroup size was reached; once the group become too large, the outcomes decreasedwith additional increases in the group size.

According to Pagell and LePine’s study (2002), research on team compositiongenerally attempts to link the characteristics of individuals who compose the teams to


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team processes and outcomes. They suggested that heterogeneity promotesperformance if the task requires a variety of knowledge, skills, abilities or othercharacteristics, and homogeneity promotes performance when the task requires a greatdeal of interpersonal interaction. In addition, there are some studies done on team sizethat found that a team should be composed of the minimum number of individuals todo the task, however, increased above this minimum can create process losses thatdetract from performance (Steiner, 1972, as cited by Pagell & LePine, 2002).

According to Lovelace et al. (2001), team functional diversity does not alwayshave positive effects on performance (cf. Ancona & Caldwell, 1992a, 1992b;Bettenhausen, 1991; Jehn, 1995, 1997; Kanter, 1988; Simons, Pelled, & Smith, 1999).In a review, Bettenhausen (1991, as cited by Lovelace et al., 2001) concluded that theoverall effect of diversity on team performance is negative, especially in times ofcrisis or rapid change, because the advantages provided by multiple perspectives areoften offset by problems generating consensus. New product team researchers havefound similar results. In the same study (Lovelace et al., 2001), it is reported thatAncona and Caldwell (1992a: 338) concluded that functional diversity might result inteams that had less flexibility, had less capacity for teamwork, were more open topolitical and goal conflicts between functions, and had more difficulty in achievingconsensus. Hence, this leads to the second hypothesis and subhypotheses:

H2: Team characteristics correlates negatively with team effectiveness.H2a: Team size correlates negatively with team performance.H2b: Team functional diversity correlates negatively with team performance.H2c: Team size correlates negatively with team member satisfaction.H2d: Team functional diversity correlates negatively with team member

satisfaction.

Internal Group Dynamics and Team Effectiveness

Lurey and Raisinghani (2001) in their study on best practices in virtual teams foundthat several dimensions in internal group dynamics were strongly positively correlatedto the effectiveness of the teams. As cited in Pawar and Sharifi’s (1997) study, thesuccessful use of teams is neither new, nor is it unique to concurrent engineering. Theearly “human relations” studies including the “Hawthorne experiments” andTavistock’s “social-technical” systems have highlighted the extent that groups’interactions, their cohesion and conformity could enhance their performance in thework place. According to Pauleen and Yoong (2001), the link between teameffectiveness and team member relationships is an important area of study in virtualteams. Stronger relational links have been associated with higher task performance(Warkentin and Beranel, 1999) and the effectiveness of information exchange(Warken et al., 1997).

As cited by Potter et al. (2000), a study by Watson and Michaelsen (1988) showedthat a team’s interaction style could affect performance. Group interaction styles aretheorized to affect performance because they can impede or enhance team members’ability to bring their unique knowledge and skills to bear on the task, and the extent towhich they develop and consider alternative strategies for approaching the task(Hackman & Morris, 1975, as cited by Potter et al.). In general, group interactionstyles affect communication and thus team performance by facilitating or hinderingthe exchange of information among team members.

Klimoski and Hayes’s (1980) study, as cited by Miles and Mangold (2002), foundthat the amounts of effort subordinates expend on the job, as well as their


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performance and work satisfaction, are influenced by the attitudes and behaviors oftheir supervisors. This suggest that a positive relationship between team leaders andteam members in imperative to the well being of the organization. According to Milesand Mangold, there are other researches that have focused on social interaction amongteam members and its contribution to satisfaction. Campion et al. (1993), as cited byMiles and Mangold, found a significant positive correlation between employees’satisfaction and the presence of communication and cooperation between groupmembers. Positive and significant correlations were also found between employeesatisfaction and workload sharing and between employee satisfaction and socialsupport. Similarly, Campion et al. (1993) found a positive correlation betweenemployee satisfaction and the level of communication and cooperation within thework groups. With the above literature review, the following hypothesis andsubhypotheses have been formulated:

H3: Internal group dynamics correlates positively with virtual team effectiveness.H3a: Quality of team member relation correlates positively with team

performance.H3b: Quality of team member relation correlates positively with team member

satisfaction.H3c: Quality of team leadership correlates positively with team performance.H3d: Quality of team leadership correlates positively with team member

satisfaction.H3e: Extent of face-to-face communication correlates positively with team

performance.H3f: Extent of face-to-face communication correlates positively with team

member satisfaction.H3g: Extent of social communication correlates positively with team

performance.H3h: Extent of social communication correlates positively with team member

satisfaction.H3i: Electronic communication correlates positively with team performance.H3j: Extent of electronic communication correlates positively with team

member satisfaction.

Team Characteristics, Internal Group Dynamics and Team Effectiveness

According to Keller (2001), the use of cross-functional groups can result in negativeoutcomes. In the same study, it stated that Lawrence (1997) critiqued the modeldevelopment and research on functional diversity and other organizationaldemographic variables as placing a “black box” between a demographic variable andoutcomes. She argued that intervening subjective or process variables would addexplanatory variance to theory about functional diversity and outcomes.

Harris and Harris (1996) found that team performance is highest when thedynamics of group process can occur; and this is more likely to happen when thenumber of participants is limited for maximum interchange. This suggests thatinternal group dynamics could be the mediating variable that enables the influence ofteam characteristics on team effectiveness. Thus, the following hypothesis is formed:

H4: Internal group dynamics mediates the relationship between teamcharacteristics and team effectiveness.


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Methodology

This is a cross-sectional correlational field study, conducted in an uncontrivedenvironment. There is no strict control on the specific type of virtual teams, includingboth ad hoc and longer-term virtual teams, as well as on the proportion of teammembers working from remote sites. The unit of analysis was team and data wasobtained by means of a questionnaire from individual respondents working in virtualteams. A sample of about 90 virtual teams from multinational companies in Penangwould serve as the respondents in this study based on Roscoe’s (1975) rules of thumbfor determining sample size (Sekaran, 2000) where it should be preferably 10 times ormore as large as the number of variables in the study.

Measuring Instruments

Team Characteristics

There are two dimensions in team characteristics: team size and functional diversity.Team size is measured by requesting the respondents to specify the total number ofteam members in the virtual team that they are referring to in the response in theSection A of the questionnaire.

Functional diversity is measured by an entropy-based diversity index that measuresthe degree of distribution across functional areas using the mathematical equationdefined by Teachman (1980), and used by Ancona and Caldwell (1992), later byLovelace et al. (2001), and Keller (2001) (as cited by Lovelace et al., 2001; Keller,2001).

( )Â=

-=s

iii PPH

1

ln

For team functional diversity or H for heterogeneity, if there are s possiblefunctional areas included in a team, Pi is the probability that the team will be found inthe ith functional area. Pi represents the fractional share of the team that is assigned toeach functional area. When an area is not represented, the value assigned to it is zero.Thus, the diversity index represents the sum of the products of each function’sproportion in the team and the natural log of its proportion. Under this formula, thegreater the distribution of team members across different functional units, the higherthe score would be for functional diversity. A minimum of zero indicates that thereare teams that consist of people from the same functional area, but from different sitesor organizations. Thus, teams with zero functional diversity are not cross-functionalteams. The higher the value indicates the more functionally diversed is the virtualteam.

This dimension is measured through respondents’ answer to Question 15 inSection A of the questionnaire, where the break down of team members in eachfunctional area is specified.

Internal Group Dynamics

The internal group dynamics is measured by adapting from the questionnaire used byLurey and Raisinghani (2001) in their study. There are 28 5-point Likert scalequestions in Section B of the questionnaire that mainly concentrates on team member


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relations and team process, which are used to measure the five dimensions of internalgroup dynamics in this study: team member relations, team leadership, face-to-facecommunication, social communication and electronic communication. Respondentswill answer the question by indicating their level of agreement to the statement stated,ranging from 1 for ‘Strongly Disagree’ to 5 for ‘Strongly Agree’. The average of theitems representing each variable will be taken as the score to indicate the level of thevariable.

Team Effectiveness.

Team effectiveness is operationalized by adapting the questions from Lurey andRaisinghani’s (2001) study. There are nine 5-point Likert scale questions in Section Cof the questionnaires. The first four questions concentrate on the overall performanceof the virtual team, while the other five questions focuses on team members’satisfaction of working in the virtual team.

Findings

A total of 340 copies of questionnaires were distributed, of which 279 weresuccessfully returned. The response rate is 82.06%. From the 279 responses, 11 wererejected due to incomplete data and 14 were received very late after the conclusion ofthe data analysis. A total of 254 questionnaires were used, and these consist of 152teams, in which 102 were pairs, while the other 50 were singles. (The 50 singles arethe ones that only one team member responded) Table 1 presents the demographicand background of the respondents who participated in this survey and Table 2 showsthe information of the organizations that involved in this study, whereas Table 3analyzed the information regarding the virtual teams in this research.


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Table 1Respondents Profile

Profile Description Frequency PercentAge Below 25 years 31 12.20

26-30 years 118 46.46

31-35 years 72 28.35

36-40 years 24 9.45

Over 40 years 6 2.36

Gender Male 170 66.93

Female 84 33.07

Ph. D 1 0.39Education Level

Master Degree 25 9.84

Bachelors Degree 190 74.80

Diploma 36 14.17

Certificate 1 0.39

High School and below 1 0.39

Top Level of Management 1 0.39

Middle Level of Management 59 23.23

Lower Level of Management 89 35.04Management Level

Non-managerial 105 41.34

Below 1 year 19 7.48

1-2 years 69 27.17

3-4 years 44 17.32

5-6 years 58 22.83

7-8 years 29 11.42

Working experience inthe organization

9 years and Above 33 12.99

0 13 5.12

1 63 24.80

2 49 19.29

3 50 19.69

4 19 7.48

5 33 12.99

No of Local TeamsJoined

> 5 25 9.84

0 4 1.57

1 95 37.40

2 62 24.41

3 38 14.96

4 20 7.87

5 24 9.45

No of Virtual TeamsJoined

> 5 8 3.15


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Table 2Organizations Profile

Profile Description Frequency PercentSemiconductor/IC products 82 32.28

Electrical products 15 5.91

Computer products 132 51.97

IT products 4 1.57

Sector of Organization

Others 21 8.27

America based 232 91.34

Japan based 3 1.18

German based 12 4.72

Malaysia based 1 0.39

Parent OrganizationBase

Others 6 2.36

Table 3Virtual Teams Profile

Profile Description Frequency Percent

Below 5 22 14.47

6-10 70 46.05

11-15 25 16.45

16-20 12 7.89

Team Size

Above 20 17 11.18

1 28 18.42

2 39 25.66

3 26 17.11

4 19 12.50

5 7 4.61

No. of Departments inTeam

> 5 27 17.76

2 67 44.08

3 33 21.71

4 21 13.82

5 11 7.24

No. ofOrganizations/Sites inTeam

> 5 20 13.16

Below 1 year 70 46.05

1-2 years 39 25.66

2-3 years 11 7.24

3-4 years 17 11.18

4-5 years 5 3.29

Time Length Team inExistence

Above 5 years 7 4.61


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Short Term 37 24.34Team Duration

Long Term 115 75.66

Team Member 182 71.65

Team Leader 43 16.93

External Team Supporter 17 6.69

Respondents' Role inTeam

Others 12 4.72

Yes 98 38.58Respondents JoinedTeam since Team'sInception

No 156 61.42

Table 4 provides the summary of the descriptive statistics of the major variables inthis study while Table 5 and Table 6 present the bivariate correlation using PearsonCorrelation done on the major variables of this study to determine the relationshipsamong the dependent variables and the independent variables.

Table 4Descriptive Statistics of Major Variables

Major Variables Mean Std. DeviationFunctional Diversity 0.90 0.63

Team Size 13.30 14.71

Team Member Relations 3.92 0.41

Team Leadership 3.85 0.45

Face-to-Face Communication 3.25 0.82

Social Communication 3.14 0.65

Electronic Communication 4.00 0.61

Team Performance 3.71 0.49

Team Member Satisfaction 3.83 0.44

Task Complexity 3.88 0.50

Table 5Correlations between Team Characteristics and Internal Group Dynamics

Functional Diversity Team Size

Functional Diversity 1.00 .24**

Team Size .24** 1.00

Team Member Relations .02 .05

Team Leadership -.14 -.02

Face-to-Face Communication -.04 .17*

Social Communication -.04 .07

Electronic Communication -.12 .00

** p< 0.01, * p< 0.05


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Table 6Correlations between Team Characteristics, Internal Group Dynamics andTeam Effectiveness

Team Performance Team Member SatisfactionFunctional Diversity .02 .03

Team Size -.08 .05

Team Member Relations .45** .69**

Team Leadership .28** .52**

Face-to-Face communication .01 .26**

Social Communication .13 .35**

Electronic Communication .18* .20*

** p< 0.01, * p< 0.05

Hypotheses Testing

All the hypotheses were tested using multiple regressions. In order to accept aregression model as valid, all five assumptions that need to be fulfilled have beenverified. The relationship is linear, the error term has constant variance, normal andindependent. There is no auto correlation problem and all the independent variablesare independent. All outliers that are beyond 2.50 standard error from mean have beeneliminated from the regression analysis.

H1 investigates the negative relationships between team characteristics and internalgroup dynamics. Five separate multiple regressions have been run to test for thishypothesis as there are five dimensions of the dependent variable. Summaries of theresults are as stated in Table 7. From the summary table, it is obvious that there is nosignificant influence of the team characteristics on the team’s internal groupdynamics. The coefficient of determination, R-square, for the models ranges from .00to .03, and the significance level are far higher than 5% for all five models. With theabove result, it is concluded that H1 is not supported. Similarly, all the sub-hypothesesare not supported as well.


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Table 7Multiple Regression Results for Team Characteristics versus Internal Group

Dependent Variable

Internal Group Dynamics

Team MemberRelations

TeamLeadership

Face-to-FaceCommunication

SocialCommunication

ElectronicCommunication

R Square .02 .03 .03 .00 .01

Sig. .34 .16 .15 .80 .52

Indep. Var

TeamCharacter-istics

Standardized Coefficients (Beta)

FunctionalDiversity 0.10 -0.14 0.02 -0.02 -0.10

Team Size 0.06 -0.06 0.16 0.06 0.01

** p< 0.01, * p< 0.05

H2 investigates the negative relationships between team characteristics and teameffectiveness. Two separate multiple regressions have been run to test for thehypothesis as there are two dimensions in team effectiveness. The similar assumptionsverifications have been done and the outliers eliminated. The summary are as in Table8. From the summary table, it is obvious that there is no significant influence of theteam characteristics on the team’s effectiveness at a .05 significance level. Thecoefficients of determination, R square, for both models are .01. As a result, it isconcluded that H2, as well as all its sub-hypotheses are not supported.

Table 8Multiple Regression Results for Team Characteristics versus Team Effectiveness

Dependent Variables

Team Effectiveness

Team Performance Team Member Satisfaction

R Square .01 .01

Sig. .58 .59

Indep. Vars. Std. Coefficients (Beta)Team Characteristics

Functional Diversity 0.07 0.06

Team Size -0.08 0.05

** p< 0.01, * p< 0.05

H3 investigates for the existence of positive relationships between internal groupdynamics and virtual team effectiveness. The summary is as reported in Table 9. Bothmodels of regression with internal group dynamics as the independent variable versus


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team performance and team member satisfaction as the dependent variables aresignificant at 1% significance level. This indicates that internal group dynamicssignificantly impact the team effectiveness. Thus, H3 is supported. In terms of sub-hypotheses, it is found that team member relations correlate positively to both teamperformance and team member satisfaction at 1% significance level. Team leadershiponly correlates positively to team member satisfaction at 1% significance level.Electronic communication is found to have negative impact on team membersatisfaction at 5% significance level. As a conclusion on the sub-hypotheses, only H3a,H3b and H3d are supported, while H3j is not supported due to the negative impactinstead of positive on team member satisfaction.

Table 9Multiple Regression Results for Internal Group Dynamics versus TeamEffectiveness

Dependent Variables

Team Effectiveness

Team Performance Team Member Satisfaction

R Square .21 ** .66**

Sig. .00 .00

Indep. Vars. Std. Coefficients (Beta)

Team Member Relations 0.39 ** 0.65 **

Team Leadership 0.12 0.29 **

Face-to-Face Communication -0.05 0.04

Social Communication -0.00 0.05

Electronic Communication 0.02 -0.11 *

** Significant at .01 level (2-tailed)

* Significant at .05 level (2-tailed)H4 investigates the role of internal group dynamics as a mediator between team

characteristics and virtual team effectiveness. A variable may be considered amediator to the extent in which it carries the influence of a given independent variable(IV) to a given dependent variable (DV). According to McKinnon et al. (1995),mediation is generally present when:

1. The IV significantly affects the mediator (Attitude);2. the IV significantly affects the DV in the absence of the mediator;3. the mediator has a significant unique effects on the DV; and4. the effect of the IV on the DV shrinks upon the addition of the mediator to the

model. Baron and Kenny (1986) has formulated the steps and conditions toascertain whether full or partial mediating effects are present in a model.

However, from the previous hypotheses testing that have been done, the resultfrom H1 and H2 have shown that the models for these two relationships do not exist.Since there are no relationships between team characteristics and team dynamics, andbetween team characteristics and team effectiveness, hence, it can be inferred thatinternal group dynamics do not mediate the relationships between team characteristicsand virtual team effectiveness.


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The summary of findings indicated that team characteristics do not have significantimpact on internal group dynamics and team effectiveness. Although the regressionmodel for H3 for internal group dynamics versus team effectiveness is significant, acloser investigation on the coefficients reveals that only team member relationscorrelates positively to team performance, while only team member relations, andteam leadership correlates positively to team member satisfaction. On the other hand,electronic communication actually correlates negatively with team membersatisfaction at 5% significance level. H4 that relates to the mediating role of teamdynamics in the relationship between team characteristics and team performance isalso not supported, even though H3 and the regression model for team characteristicsand internal group dynamics versus team effectiveness is significant.

Discussion

Impact of Team Characteristics on Internal Group Dynamics

The results from the testing of Hypothesis 1 show that both team size and teamfunctional diversity does not influence internal group dynamics. Based on theliterature findings, there are generally two schools of thought on team size’s influenceon internal group dynamics. Some past researchers found that when a team’s sizeincreases over 20, the team dynamics decreases (Bal & Teo, 2000; Stoel, 2002). Onthe other hand, another group of researchers were of the opinion that it isinappropriate to limit the team to a specific size as it needs to be large enough to havethe skills and expertise to get the task completed, while technology has made it easierfor people to communicate and feel less inhibited about offering new thoughts andopinions (Duarte & Snyder, 2001; Harris & Harris, 1996). Thus, there is no ‘right’size for a team, although they do not reject the potential negative impacts that mayoccur.

This suggests that in this study’s context for a virtual team, the second school ofthought seems to be prevalent. This finding could be due to a few reasons. Firstly, asstated in the previous section, a team needs to be big enough to encompass all theskills and resources required for a specific task. Thus, a small team can be verylimited in terms of skill sets, while a larger group has more potential to work on morevariety of tasks or larger projects. Although, as team size grows bigger, teammembers tend to form subgroups (Duarte & Snyder, 2001), and this could possiblycreate conflicts among these subgroups and affects the team member relations.However, with the ease of technology usage for most of the hi-tech multinationalcorporations, in which the sample of this study is based on, this has seemed to beovercome. This coincides with Duarte and Snyder’s (2001) claimed that technologymakes a larger impact on larger groups than with smaller groups. Due to this, thepositive effects and negative effects could have compensated each other and thus theoverall impact on team dynamics has become insignificant. This may also indicatethat the relationship between team size and effectiveness is actually non-linear, whereeffectiveness increases with size up to an optimal value beyond which theeffectiveness will decrease.

In addition, another possible reason could have been the nature of virtual teamitself. Although there are many members in the team, most of the time thecommunication could have been dominated by a few key players. Thus, although the


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actual team size is large, the number of active team members is limited (Lipnack &Stamps, 1997, as cited in Bal & Teo, 2000). As a result, the potential negative impactof large team size is not experienced by the team members. This does not affect teammember relations, team leadership, and all means of communications for groupdynamics.

On the other hand, the first school of thought of past researches on team size couldhave been proven true in this study as well. The non-impact of team size on internalgroup dynamics could have been due to the data obtained for this study. It is observedthat about 77% of the team sizes collected in this study is of size 15 members or less(Table 3) and the overall mean is only approximately 13 members in a team (Table 4).Only a small percentage of the teams are having more than 15 members in a team.The mean of the team size in this study has not met the limit of 20 as set by some pastresearchers that could have hindered group dynamics. Thus, the negative impact couldnot be observed in this study.

Similarly, in terms of team’s functional diversity, there are also two main schoolsof thoughts. Some argued that highly functional diversified team has the advantage ofmultiple resources and skills (Lovelace et al., 2001; Pauleen & Yoong, 2001; Pawar &Sharifi, 1997; Sosik & Jung, 2002), while others see it as a potential hindrance togroup dynamics (Church, 1995; Duarte & Snyder, 2001). Proehl (1997) and Keller(2001) addressed both positive and negative impacts of functional diversity of team.

However, the findings from Hypothesis 1 show that both positive and negativeimpacts could have compensated each other in the virtual team settings, producing aneutral (and therefore insignificant) impact on team dynamics in this research’scontext. This provides answers to the research question that team characteristics donot influence team dynamics.

Beside the reasons mentioned above, functional diversity is the essence and thenature of a virtual team. Thus, the multinational corporations that adopted virtual teamcould have been very cautious when implementing this concept in the organizations.As a result, the team members could have been provided with sufficient training andpreparations prior to the forming of the virtual team. Hence, the negative impact offunctional diversity does not prevail and the team members’ relations are not affected.

In addition, as observed in Table 3, most of the team consists of members from oneor two departments (44.08%), and involving only two different sites or organizations(44.08%). This indicates that the diversity levels of the teams are quite low. Thus, thepossible negative impact of highly functional diversified team on team dynamics isnot easily observed in this study. Furthermore, it is observed that 75.66% of thevirtual teams in this study are long term, while only 46.05% of the virtual teams havebeen in existence for less than a year. More than 50% of the teams have been inexistence for more than a year suggests that most of these teams could have beenworking together repeatedly for long enough to build up the understanding and goodrelationships among themselves, and have a strong trust among each other to work onthe assigned tasks. Consequently, the team members work together well andcompensated the possible team dynamics lost due to functional differences andconflicts.

Impact of Team Characteristics on Team Effectiveness

Findings from Hypothesis 2 show that the impact of team size and functional diversityon team effectiveness is insignificant. Similarly, team size and functional diversity are


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claimed to have different impacts on team effectiveness by different researchers.Some found that team composition which are big and functionally diversified wouldinevitably lead to a decrease in overall team performance (Castka et al., 2001; Church,1998; Lovelace et al., 2001; Stoel, 2002), while others take this as an opportunity forbetter performance due to the diversified skill sets available. However, they did notdeny the potential negative impact from bad team composition (Pagell & LePine,2002).

This could be due to the virtual team context that this study is based on. Since teamsize and functional diversity has become the main reasons why most organizationsadopt virtual team, the team formation process could have been carried out with greatcaution, and as such, the negative impact does not prevail. In addition, as statedabove, the mean team size of this study is less than 15, the functional diversity is nottoo high, and the team members are well selected; therefore, the potential negativeimpact has been found to be insignificant. Thus, indicating that team characteristicsdo not influence team effectiveness in this study.

Impact of Internal Group Dynamics on Team Effectiveness

From the findings for Hypothesis 3, it is found that internal group dynamics influenceteam effectiveness significantly. Stronger positive internal group dynamics will bringbetter team effectiveness. However, among the five dimensions of internal groupdynamics in this study, it is found that team member relations play the most importantrole in promoting team performance and team member satisfaction. This coincideswith the findings of most past researches (Lurey & Raisinghani, 2001; Pauleen &Yoong, 2001; Pawar & Sharifi, 1997; Potter et al., 2000). Thus, virtual team that hasstrong team member relations tends to perform well in the task assigned to them, aswell as promote the satisfaction amongst the team members. This is very reasonableas psychologically, team members that do not feel satisfied working in the team willhave difficulty performing the tasks given effectively.

In addition, it is also shown that strong team leadership will enhance team membersatisfaction. This is similar to the findings of Klimoski and Hayes (1980) as cited inMiles and Mangold (2002). Thus, the role and influence of a virtual team leadershould never be neglected. The ability of an organization to choose the appropriatecandidate to lead a team will determine the success of the virtual team.

On the other hand, instead of having positive impact on team effectiveness,electronic communication is found to negatively influence the overall teamperformance. This could be due to the missing human touch when electroniccommunication is used too extensively. No doubt the proper use of electroniccommunication could improve communication among virtual team members, but thebenefit does not prevail when team members feel less satisfied working in the team.Thus, to answer the research question, strong internal group dynamics correlatespositively to team effectiveness. As internal group dynamics improves, the teameffectiveness improves in the similar directions.

Meanwhile, from the findings of Hypothesis 2, it is observed that face-to-facecommunications and social communications do not impact team effectiveness. It isinsignificant because there is not much variation on these two variables. This could bedue to the recent slow down on the global economic condition. As the business cyclehits the trough, most multinational companies have cut down on travel, thus have notspared enough funding to facilitate face-to-face communication and social


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communication. As a result, face-to-face meetings and social activities have beenreduced, causing the opportunity to experience the benefits of face-to-facecommunication and social communication to be minimum, thus lack of variation.

Limitations

Although this research has managed to achieve its stated objectives, there are somelimitations that have been observed. Due to time and resource constraints, this studyhas chosen to select a limited sample from the manufacturing multinationalcorporations in the proximity. Thus, this has excluded the possible differences thatcould be observed when service industries are included. Therefore, the findings fromthis study may not be generalized to the service industry. In addition, due to thedifferences in the size of the multinational organizations in the proximity, the findingsmay be slightly biased towards the bigger corporations where more virtual teams areavailable for sampling of this research.

Furthermore, although virtual teams consist of members from anywhere in theworld, all respondents to this research come from local site which are more easilyaccessible. As a result, the virtual teams are mostly represented through Malaysians’perception. Since Malaysians are used to living in the environment with people frommultiple cultural backgrounds, they are high on collectivism (Hofstede, 1980, as citedin Kennedy & Mansor, 2000) and could have higher tolerance and acceptance level oncultural differences (Abdullah, 1992, as cited in Jaouadi, 2000), thus affect theoutcome of this study. In addition, some of the virtual teams are represented by onlyone respondent per team, due to the formation of the virtual teams of one member persite, this may pose some bias to the response to be used to represent the team.However, for teams that are represented by dyads, there has been a great challenge toensure that the two respondents are responding to the questions posed based on thesame teams without being affected by their experiences in other virtual teams.

In addition to the above, there are some gray areas identified in this study withreference to the definition of virtual teams. There are different levels of virtualteaming. Some teams consist of only one or two members from other locations withmajority of team members from one site, while others have members spanning acrossmany different locations evenly. Some teams involve only two sites while othersinvolves up to more than five site locations. However, this study does not includeteams with all members from the same sites, but separated by different offices someblocks away, in the same building at more than 50 feet apart as defined by Pape(1997) as cited by Johnson et al. (2001). In addition, there are some virtual teams thatare very informal in nature. These teams only meet and discuss their problems as itarises, and ends as soon as the problem is resolved in a very short term. As a result,these teams may have very different experiences as compared to longer-term virtualteams that have been formally formed.

Finally, in this study, there is no measurement done on the frequency of face-to-face meetings of virtual teams. Therefore, we cannot assess what is the virtual level ofa team. Some teams may have very frequent face-to-face meetings while others neverhave any. These may potentially affect the overall findings of this study because someof the respondents may have dealt with the same group over and over so frequentlythat they are so familiar with each other that even without face-to-face meeting nowdo not affect the team members’ relations and team effectiveness. In addition to allthe above mentioned, it is important to observe that the sample size for this study is


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quite small, thus could have limited the generalizability of this study to othercountries or industries.

Conclusion

This study was primarily set to examine virtual team effectiveness, and its influencesfrom team characteristics, and internal group dynamics. Despite the variousconstraints to this study, the results have been encouraging as it has manage to shedsome light for managers and organizations so as to better manage their virtual teamsin order to achieve their objectives and goals for competitive advantages.

It is important for managers to maintain proper composition and characteristics ofthe virtual team, while concentrate more effort on the team member relations andteam leadership to promote better team dynamics. Communications among teammembers need to be handled with care. Excessive communication using the wrongmeans, such as electronic communications, may have negative effects and causesdissatisfaction among team members.

Virtual team will continue to be the choice for corporations to stay ahead of alltheir competitors in terms of time and effectiveness. At the same time, increasingly,the conventional co-located (face-to-face) teams will endeavor to improve itsperformance and effectiveness by imitating some of the technologies and thecharacteristics of virtual team. In the near future, there may not be any distinctionbetween the two due to the pervasive nature of technology throughout most modernorganizations. Thus, this study will serve as a guideline to not only the virtual teamsalone, but all other conventional co-located teams as well.

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About the Authors

T. Ramayah has taught courses in Statistics, Operations Management, ResearchMethods, Forecasting and Computer Literacy at the undergraduate level. He hassupervised numerous MBA students in the fields of Information Systems, OperationsManagement, Marketing Management and Organizational Behaviour. He is alsocurrently supervising numerous students at the MA and PhD levels. He has alsopresented numerous papers at local and international conferences. He is also active inresearch publications having published research papers in several local andinternational journals of repute. He is currently Head of Department ofProduction/Operations Management, School of Management, Universiti SainsMalaysia.Prof. Muhamad Jantan is formerly a lecturer at the School of MathematicalSciences, and School of Management, with research interest in technologymanagement. He has presented and published papers in international conferences inthis area, and areas related to operations management. Currently, he is director of


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Centre for Policy Research, which primarily looks at policies for the nationalgovernment.Dr. Aizzat Mohd. Nasurdin has taught courses in Organizational Behavior at theundergraduate level. She has supervised numerous MBA students in the fields ofOrganizational Behaviour. Se is also currently supervising numerous students at theMA and PhD levels. She has also presented numerous papers at local andinternational conferences. She is also active in research publications having publishedresearch papers in several local and international journals of repute. She is currentlyHead of Department of Organization Section, School of Management, UniversitiSains Malaysia.Ms Koay Hooi Ling was a postgraduate from Universiti Sains Malaysia. Herresearch focused on Virtual Teams composition and dynamics and its impact oneffectiveness in her Master of Business Adminstration (MBA). She currently serves inone of the MNCs in Penang, Malaysia.

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